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Short on time? Don't miss out. Here are the key highlights:
- Data has long been a challenge for organisations as they struggle with quality, scalability, democratisation and autonomy
- Data mesh overcomes these challenges through its four principles; data as a product, decentralisation, self-serve data infrastructure and data governance
- The benefits of data mesh are plentiful - scalability, agility, autonomy, faster time to value, collaboration and quality
The data dilemma
Data has long been considered the lifeblood of modern organisations. It fuels analytics, informs strategy and enables businesses to gain a competitive edge. But, as data volumes have grown exponentially, many organisations have found themselves grappling with several common challenges: data silos, scalability, quality and democratisation. According to the Nash Squared Digital Leadership Report, only one in four digital leaders are confident that they are using their data effectively for insights and this can be owed in part to inefficient data management practices.
This is where data mesh comes into play. Data mesh is a groundbreaking concept born out of the necessity to tackle the challenges posed by the deluge of data. Coined by Zhamak Dehghani, data mesh is not merely a response to this data boom but a revolutionary approach to data management that challenges the long-standing centralised data architectures. In this article, we discuss the principles underpinning the data mesh approach, benefits that its application can bring to your organisation and example use cases.
Introducing the data mesh approach
At its core, data mesh advocates for decentralisation, treating data as a product and empowering domain-specific teams to take ownership of their data. It's a philosophy that addresses the limitations of traditional data warehouses and data lakes by reimagining data management.
Principles underlying data mesh
If you should remember anything, it's that the success of data mesh relies on four key principles. We take a look at these in more detail.
Principle one: data as a product
Firstly, data as a product. Data mesh encourages organisations to treat data as a product. This means shifting the perspective from viewing data as a mere resource, to treating it with the same care and attention as any other product. Just as a product undergoes rigorous development, testing and iteration, data should also be managed with a similar focus on quality and utility.
Principle two: decentralisation and domain-oriented ownership
Principle two, data mesh advocates decentralisation by distributing ownership and management of data from warehouse teams to cross-functional domain teams. Thus, allowing domain teams (such as marketing, procurement, etc) to access, understand and extrapolate data without relying solely on central data teams. Why should this interest a business leader? Because decentralisation enables faster domain-decision making and responsivity to business needs.
Principle three: self-served data infrastructure
We all know that there is a significant skill shortage pertaining to data literacy and analytics. The nature of self-served data infrastructure means that platforms should be easy to navigate and data easily accessible even by non-technical data users. As such, domain teams are able to build, maintain and evolve their own data products without the complications of navigating limited and overly technical infrastructures. This shift from a centralised model empowers teams to have autonomy over their own data, reducing bottlenecks and accelerating the delivery of insights.
Principle four: federated data governance
The final principle, data mesh introduces federated data governance, wherein domain teams collaborate on defining data standards, quality and compliance within their domains. This approach democratises governance, ensuring that those closest to the data are responsible for its integrity and quality.
Data mesh yields many benefits for organisations
The adaptability of data mesh makes it relevant and valuable across a wide range of industries, offering a pathway to more efficient data management and data-driven decision-making. When executed well, the data mesh approach presents a number of opportunities for organisations, relating to cost optimisation, enhanced data-driven insights and quality. This is because it encourages domains to take active responsibility in driving data value and in the end, organisational success. So how can data mesh benefit your organisation?
Improving data autonomy and collaboration cross-business
The nature of decentralised ownership grants your domain teams greater autonomy and control over their data, leading to quicker decision-making and better domain-specific insights. Moreover, this shared responsibility across your teams fosters a culture of collaboration, encouraging responsibility of data quality, analysis and outputs.
Increasing scalability and agility
The proliferation of IoT (Internet of Things) devices, 5G, social media and global internet has ushered in an era of unprecedented data generation. Billions of interconnected devices across industries are producing an overwhelming amount of data every second. Where traditional warehouses would fall short, data mesh is flexible and allows your organisation to scale efficiently by distributing data responsibilities and fostering innovation within domain teams. This agility is critical in responding to rapidly changing business environments.
Delivering faster time to value
The self-serve data infrastructure reduces bottlenecks by enabling domain teams to independently manage and deliver data products, accelerating the time to insights and value. Teams are able to access critical data faster and deliver faster outputs. In manufacturing for example, data mesh can optimise production processes by providing real-time insights into machine performance and product quality.
Enhanced data quality
According to a survey conducted by Capital One, 82% of organisations voted confusing or lack of clear data governance policies as a top challenge. With federated data governance, your domain teams become stewards of data quality, ensuring that data remains dependable and compliant within their domains.
Data mesh in action - a success story
Let's take a look at an example of data mesh in action. An American multinational logistics corporation wanted to build a scalable data mesh, to enable them to view data as a product, rather than a by-product and solve challenges of legacy data management systems. Once transitioning to decentralisation, the organisation observed greater data quality and visibility of data issues as they arose. The data governance principles provided them with greater scalability and confidence to democratise access to trusted data. Since shifting to data mesh with NashTech, 5.5x more people are using data across the business regularly.
Partner with NashTech
At NashTech we can help you transition from rigid and centralised data management systems to the scalable data mesh approach. Our suite of tools, architecture and data experts can help your organisation overcome bottlenecks presented by traditional warehouses and get the most out of your data.
Drive your business forward with data-driven insights. Discover our data mesh solutions here.
